Every scraper you build today is technical debt

It works today.

Then the website changes.

Your selectors break.
Your proxy costs go up.
Your CAPTCHA rate goes up.
Your parser breaks.

And now someone on your team owns a scraper forever.

One scraper becomes three.

Three become ten.

And suddenly your AI product has a whole engineering team maintaining infrastructure that has nothing to do with the product you're actually building.

But AI agents are going to need more web data, not less.

LinkedIn for leads.
Reddit for conversations.
X for real-time signals.
Amazon for products and pricing.
Google Maps for places and businesses.
Search for everything else.

Are we going to build a separate scraper for every source an agent needs?

Maybe web scraping shouldn't be an application feature. Maybe it should be infrastructure.

That's the idea behind Mindcase.

We built Mindcase to give AI agents access to anything on the web through APIs.

Instead of:

website → browser → scraper → proxy → parser → maintenance

it's:

agent → Mindcase API → structured data

One API per task.

Use it from your code, run it directly, or connect it to your AI agent through MCP.

What web data are you currently scraping that you wish you could just call through an API?